CONCEPT
Problem Space
The formal structure of a problem — initial state, goal state, operators, constraints — that Simon and Newell argued was the proper unit of analysis for understanding how bounded minds solve problems, and whose AI-era expansion demands corresponding expansion of the builder's representation discipline.
A problem space is the formal representation of a problem as a set of states, operators that transform states, an initial state (where the solver starts), a goal state (where the solver wants to arrive), and path constraints (the conditions that any valid solution must satisfy). Simon and Newell introduced the framework in Human Problem Solving (1972) as the proper unit of analysis for cognitive research: what the solver is solving, not merely what the solver is doing. The problem space for any non-trivial problem is too large to search exhaustively — chess has more positions than atoms in the observable universe, software architecture has more configurations than any mind can enumerate — so the solver must use heuristic search to navigate the space toward the goal. The quality of the navigation depends on the quality of the representation: well-represented problems are solvable by competent heuristics, while poorly represented problems produce energetic but